IP Library Granted Patent US 11,978,560
Granted Patent B2
US 11,978,560 · App. 17/951,421 · Granted May 7, 2024

Systems and methods to process electronic images to identify diagnostic tests

Inventors: Leo Grady (Darien, CT); Christopher Kanan (Pittsford, NY); Jorge Sergio Reis-Filho (New York, NY); Belma Dogdas (Ridgewood, NJ); Matthew Houliston (Boston, MA)
Assignee: Paige.AI, Inc.
G16H50/20G06F18/214G06T7/0012G06V10/25G06V30/19147G16H10/20G16H30/40G06T2207/20081G06T2207/30004G06V2201/03
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Quick Facts
Patent No.
US 11,978,560
App. No.
17/951,421
Granted
May 7, 2024
Kind
B2
Abstract

Systems and methods are disclosed for processing digital images to identify diagnostic tests, the method comprising receiving one or more digital images associated with a pathology specimen, determining a plurality of diagnostic tests, applying a machine learning system to the one or more digital images to identify any prerequisite conditions for each of the plurality of diagnostic tests to be applicable, the machine learning system having been trained by processing a plurality of training images, identifying, using the machine learning system, applicable diagnostic tests of the plurality of diagnostic tests based on the one or more digital images and the prerequisite conditions, and outputting the applicable diagnostic tests to a digital storage device and/or display.

Claims (39)

1. A computer-implemented method to determine applicability of one or more diagnostic tests for a patient, comprising:

receiving one or more digital images associated with a pathology specimen;

identifying at least one applicable diagnostic test among a plurality of diagnostic tests, wherein identifying the at least one applicable diagnostic test includes applying a machine learning system to the received one or more digital images to identify at least one prerequisite condition for any of the plurality of diagnostic tests to be applicable, and wherein identifying the at least one applicable diagnostic test is based on the identified at least one prerequisite condition; and

scoring the at least one identified applicable diagnostic test based on at least one predetermined preference.

2. The method of claim 1 , wherein identifying the at least one applicable diagnostic test includes producing an N-dimensional binary vector comprising one or more elements corresponding to a diagnostic test applicability.

3. The method of claim 1 , wherein the at least one predetermined preference includes at least one of:

an availability of the identified applicable diagnostic test;

a speed of the identified applicable diagnostic test; or

an out-of-pocket patient cost of the diagnostic test.

4. The method of claim 1 , wherein scoring the at least one identified applicable diagnostic test includes determining a weighted sum based on the at least one predetermined preference.

5. The method of claim 1 , wherein identifying the at least one applicable diagnostic test further comprises predicting a negative predictive value (NPV) for each of the plurality of diagnostic tests.

6. The method of claim 5 , wherein identifying the at least one applicable diagnostic test further comprises excluding at least one diagnostic test among the plurality of diagnostic tests based on the NPV for the at least one diagnostic test.

7. The method of claim 1 , further comprising outputting the at least one identified applicable diagnostic test to a digital storage device and/or a display.

8. The method of claim 1 , wherein identifying the at least one applicable diagnostic test includes identifying a plurality of applicable diagnostic tests, wherein scoring the at least one identified applicable diagnostic test includes scoring each identified applicable diagnostic test among the plurality of applicable diagnostic tests, and wherein the method further comprises:

ranking the scored identified applicable diagnostic tests.

9. The method of claim 8 , wherein ranking the scored identified applicable diagnostic tests includes producing an N-dimensional vector of scores and sorting the N-dimensional vector.

10. The method of claim 9 , wherein the N-dimensional vector includes multi-label outputs corresponding to an absence of a clinically relevant result.

11. The method of claim 10 , wherein the absence of the clinically relevant result includes an absence of a mutation or fusion of one or more biomarkers.

12. The method of claim 9 , further comprising determining a list of the scored identified applicable diagnostic tests in an order based on the ranking.

13. The method of claim 12 , further comprising removing at least one scored identified applicable diagnostic test from the list based on one or more predetermined thresholds.

14. The method of claim 1 , wherein identifying the at least one applicable diagnostic test includes identifying a plurality of applicable diagnostic tests, wherein scoring the at least one identified applicable diagnostic test includes scoring each identified applicable diagnostic test among the plurality of applicable diagnostic tests, and wherein the method further comprises:

determining, based on the identified applicable diagnostic tests and the scoring, one or more therapies.

15. The method of claim 1 , wherein identifying the at least one applicable diagnostic test includes setting a threshold configured to optimize identification of the at least one prerequisite condition.

16. The method of claim 1 , wherein identifying the at least one applicable diagnostic test includes:

filtering the one or more digital images to identify at least one tissue region of interest for analysis; and

removing a non-applicable region from the one or more digital images, the non-applicable region comprising an area not identified as a tissue region of interest.

17. The method of claim 1 , further comprising:

receiving additional information associated with the pathology specimen, the additional information including information about a patient, information about a disease, additional diagnostic test information, and/or additional test preference information.

18. The method of claim 17 , wherein at least one of identifying the at least one diagnostic test or scoring the identified at least one diagnostic test is based on the received additional information.

19. A system for determining applicability of one or more diagnostic tests for a patient, comprising:

at least one memory storing instructions; and

at least one processor configured to execute the instructions to perform operations comprising:

receiving one or more digital images associated with a pathology specimen;

identifying at least one applicable diagnostic test among a plurality of diagnostic tests, wherein identifying the at least one applicable diagnostic test includes applying a machine learning system to the received one or more digital images to identify at least one prerequisite condition for any of the plurality of diagnostic tests to be applicable, and wherein identifying the at least one applicable diagnostic test is based on the identified at least one prerequisite condition; and

scoring the at least one identified applicable diagnostic test based on at least one predetermined preference.

20. A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to perform a method to determine applicability of one or more diagnostic tests for a patient, the method comprising:

receiving one or more digital images associated with a pathology specimen;

identifying at least one applicable diagnostic test among a plurality of diagnostic tests, wherein identifying the at least one applicable diagnostic test includes applying a machine learning system to the received one or more digital images to identify at least one prerequisite condition for any of the plurality of diagnostic tests to be applicable, and wherein identifying the at least one applicable diagnostic test is based on the identified at least one prerequisite condition; and

scoring the at least one identified applicable diagnostic test based on at least one predetermined preference.

Assignments (3)
RELEASE OF SECURITY INTEREST Recorded May 14, 2026
From: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
To: PAIGE.AI, INC.
Reel/Frame 075589/0752 →
SECURITY INTEREST Recorded Oct 21, 2025
From: PAIGE.AI, INC.
To: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
Reel/Frame 073216/0876 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 30, 2022
From: GRADY, LEO; KANAN, CHRISTOPHER; DOGDAS, BELMA; HOULISTON, MATTHEW
To: PAIGE.AI, INC.
Reel/Frame 062245/0039 →
Continuity (4)
Continuation 17519834 · Nov 5, 2021
Continuation 17504867 · Oct 19, 2021
Provisional Application 63104923 · Oct 23, 2020
Related Publication 20230019631A1 · Jan 19, 2023